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Record W1906139134 · doi:10.29173/pandpr25360

"My Body Can Do Magical Things" The Movement Experiences of a Man Categorized as Obese –A Phenomenological Study

2015· article· en· W1906139134 on OpenAlexvenueno aff
Gro Rugseth, Øyvind Førland Standal

Bibliographic record

VenuePhenomenology & Practice · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMartial Arts: Techniques, Psychology, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsMartial artsMeaning (existential)PleasureEmbodied cognitionPsychologyPerspective (graphical)Interpretative phenomenological analysisValue (mathematics)AestheticsPhysical activityPhenomenology (philosophy)Social psychologyEpistemologySociologyMedicineQualitative researchArtPsychotherapistVisual artsSocial sciencePhilosophy

Abstract

fetched live from OpenAlex

From a medical perspective, exercise and physical activity are valuable tools for losing weight, through an increase in energy expenditure. However, beyond this instrumental value, physical activity has meaning for the person experiencing it. Among individuals categorized as obese, that meaning is often problematic. The aim of this paper is to produce essential knowledge about one young man's embodied experiences of practicing martial art. Through a phenomenological analysis of research material concerning the young man’s passionate relationship to martial arts, we identify ways in which someone who has a body often regarded negatively, might still derive great pleasure from his movement experiences.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.015
Scholarly communication0.0030.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.408
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

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